1. Field of the Invention
The present invention generally relates to radar systems, and more particularly, to methods and apparatuses for calibrating a radar receiver and processing radar signals reflected from a target.
2. Description of the Related Art
In World War II, radar systems using centimeter wavelengths were discovered to detect reflections from precipitation, such as rain and hail. Since this discovery, radar systems have developed into extremely useful tools for identifying and classifying weather systems, particularly in the 3 cm to 10 cm wavelength range. For example, a weather radar system is typically installed on an aircraft to identify the conditions within a weather system, such as a cloud, that the aircraft is approaching. Radar waves emitted from the aircraft's radar system reflect from precipitation in the cloud and return to the aircraft. The radar system detects and analyzes the reflected waves to identify the range and characteristics of the cloud. In particular, the power of the reflected signal is proportional to the cloud's reflectivity, which is in turn related to the amount of rainfall within the cloud. Consequently, by timing the delay between the pulse emission and detection and comparing the power of the reflected signal to a series of power thresholds, the range to and characteristics of the cloud may be established.
As the range to the target increases, however, the signal-to-noise ratio drops dramatically. Like any light waves, the intensity of a radar pulse fades in a manner proportional to the square of the distance propagated. Therefore, because reflected waves travel both to and from a target, the radar waves are attenuated in a manner proportional to the range of the target to the fourth power for a point target. For a target which completely fills the beam, the relationship is to the second power. For a target which partially fills the beams, the relationship lies between the second and fourth powers. The waves are further attenuated due to atmospheric loss and the like. As a result, the signal from distant targets is relatively weak, so that background noise and receiver generated noise, which occurs in every environment, tends to obscure the reflected signal. To extract useful information from distant target reflections, amplification and processing of the detected reflections are consequently necessary to compensate for the lower signal-to-noise ratio.
In a simple radar system configuration, detected signals are amplified according to a schedule. The radar receiver amplifies both the reflected signal and the noise, but because the reflected signal amplitude is greater than the amplitude of the noise, the amplification magnifies the difference between the signal and the noise, facilitating differentiation between the noise and the reflected signal. The gain is varied with time, according to a predetermined schedule, to take advantage of the known propagation rate of the radar pulse. After a radar pulse is emitted, the system begins to incrementally amplify the detected signals as a function of time. Because the radar pulse propagates at a substantially constant and known speed, and because the rate of attenuation is known, the level of amplification may be adjusted with time to counter the known attenuation of the reflected signals.
Typically, the gain is adjusted to maintain a threshold for the input power received from a target of a particular reflectivity at a constant level. For example, a cloud which is releasing 10 millimeters of rain per hour is known to have a particular reflectivity at a particular wavelength. The rate at which the signal attenuates with distance is also known, (based on an assumed beam-filling percentage) so the gain may be scheduled to counter the known rate of decay of the signal.
Signals received from the target are also filtered and analyzed for amplitude. The received signal is compared to a plurality of detection thresholds, each corresponding to a target of different reflectivity at the range of the target. If the amplitude of the reflected signal exceeds at least one of the detection thresholds, the relevant portion of the signal is treated as potentially relating to a relevant target.
The effectiveness of this system is limited, however, by the characteristics of radar detectors and the signals they detect. When the signal-to-noise ratio is high, the power output of the radar detector varies approximately linearly with respect to the power of the signal incident upon the antenna. As the signal-to-noise ratio decreases, however, the relationship becomes nonlinear, especially for signals received from low reflectivity targets or from very distant targets. Consequently, the constant detection thresholds and scheduled gain as described above become improperly calibrated for signals with low signal-to-noise ratios.
To provide the appropriate detection thresholds for signals with low signal-to-noise ratios, current systems adjust the detection thresholds to vary nonlinearly with respect to the power of the signal incident upon the antenna. Because the thresholds do not vary linearly, however, the thresholds are adjusted according to data tables based on empirical data. In other words, the radar system is tested in a particular configuration to assemble the relevant data as a function of time based on the hardware configuration, operating parameters, target reflectively, gain, and detection threshold. The data is then stored in a local memory for access by the radar receiver to update the gain and detection thresholds as a function of time. Thus, after a pulse is emitted, the radar detector regularly updates the system parameters by checking the appropriate table determined by the configuration of the radar system, the type of target, and the time elapsed since the pulse emission. Based on these variables, the table provides an empirically detected gain for amplifying incoming signals and a set of detection thresholds for classifying the intensity of incoming detected signals.
Although such conventional systems may be functional, creating the data table presents a time-consuming and demanding task. Empirical data for the threshold is developed for each and every time interval and adjustment of the gain. A different set of data is developed for each target of a certain reflectivity having a corresponding threshold. In addition, the data for the gain schedule and all of the thresholds correspond to only a single configuration of the radar system, such as a particular transmitter antenna and pulse power. Consequently, because the schedule for the adjustments to the gain and the threshold vary according to the hardware and configuration of the transmitter and antenna, data tables are compiled for each of the different anticipated configurations. For example, a radar system configurable with two different antennae has two different gain schedules and sets of detection threshold data tables, because the power of the pulse incident upon the target varies according to the antenna being used.
Furthermore, simply changing various operating parameters often requires new data tables. For example, changing the pulse width of the emitted pulse changes the power of the return signal from a target. As a result, the original detection threshold data no longer applies, and the system performance degrades.
As the number of possible configurations and detection thresholds increases, the number of tables that are developed and stored in the radar system also increases. This represents not only more experimental time generating the empirical data, but greater storage requirements for the data tables in the radar detector. Because such radar systems are typically used in conjunction with compact avionics systems, the addition of further memory to accommodate additional data tables not only increases the cost of the radar detector, but also presents the problem of finding sufficient space for the added memory components which must necessarily be added.